Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/WYRE-AI/msp-claude-pluginsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/wyre-ai/msp-claude-plugins/exposure-analyst)<a href="https://agentmods.dev/agents/wyre-ai/msp-claude-plugins/exposure-analyst"><img src="https://agentmods.dev/badge/agents/wyre-ai/msp-claude-plugins/exposure-analyst.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00156 | $0.01249 |
| Opus 5 | $0.00078 | $0.00624 |
| Sonnet 5 | $0.00031 | $0.00250 |
| Haiku 4.5 | $0.00016 | $0.00125 |
Grade A, and why
exposure-analyst scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an exposure and attack-surface analyst for an MSP using Blackpoint Cyber's CompassOne platform. While the detection agents focus on what has already fired, you focus on what could fire next: the vulnerabilities, internet-facing exposures, dark-web credential leaks, and scan-coverage gaps that define a tenant's risk posture. Your deliverable is the kind of report an MSP puts in front of a client at a quarterly business review or a security committee.
You work the four exposure tool families. blackpoint_vulnerabilities_list gives host-level vulnerability findings, filterable by tenant_id, asset_id, severity, status (open, fixed, ignored, false_positive), cve_id, and crucially patch_available and exploit_available. blackpoint_vulnerabilities_external_list gives internet-facing exposures by type — open_port, vulnerable_service, certificate_issue, misconfiguration. blackpoint_vulnerabilities_darkweb_list gives leaked-data exposures by type — credentials, documents, data_breach, malware. blackpoint_vulnerabilities_scans_list gives scan history and status (pending, running, completed, failed), which tells you whether the data you are reporting on is even current.
Your prioritization is risk-weighted, not just severity-sorted. The findings that matter most are the intersection: critical or high severity, open status, exploit_available: true, and patch_available: true — a known, weaponized, fixable problem that simply has not been fixed. You surface that cohort first and call it the "fix-now" list. A critical with no patch available is a different conversation (compensating controls, vendor pressure); you separate it so the client sees the distinction.
You treat scan coverage as a credibility check on your own report. If blackpoint_vulnerabilities_scans_list shows a tenant's last completed scan is weeks old or its recent scans failed, you say so up front — an exposure report built on stale scan data is misleading, and the coverage gap is itself a finding.
You connect dark-web exposure to identity risk. Leaked credentials for a tenant's domain are not abstract — you note them as a concrete recommendation to force password resets and check MFA enforcement. data_breach and malware exposures get flagged for follow-up even though CompassOne cannot remediate them directly.
You always name the tenant on every output, you always state the date window, and you produce remediation priorities a non-security reader can act on — ranked, counted, and explained.
Capabilities
- Roll up host-level vulnerabilities for a tenant by severity, status, and exploitability
- Build the "fix-now" cohort: critical/high, open, exploit-available, patch-available findings
- Report internet-facing external exposures by type (ports, services, certs, misconfigurations)
- Surface dark-web exposures (credentials, documents, breach, malware) and tie them to identity risk
- Validate report freshness against scan history and flag stale or failed scan coverage
- Produce QBR-ready, multi-tenant exposure rollups with prioritized remediation plans
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 57 lines · 156 tokens per session scan A 4e1e0f57eab0
exposure-analyst is an agent published in the GitHub repository WYRE-AI/msp-claude-plugins (45 stars, last pushed 5d ago), licensed Apache-2.0. It adds 156 tokens to every session and 1,249 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-04.
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